Autonomic computing architecture for SCADA cyber security

Cognitive computing relates to intelligent computing platforms that are based on the disciplines of artificial intelligence, machine learning, and other innovative technologies. These technologies can be used to design systems that mimic the human brain to learn about their environment and can autonomously predict an impending anomalous situation. IBM first used the term ‘Autonomic Computing’ in 2001 to combat the looming complexity crisis (Ganek and Corbi, 2003). The concept has been inspired by the human biological autonomic system. An autonomic system is self-healing, self-regulating, self-optimising and self-protecting (Ganek and Corbi, 2003). Therefore, the system should be able to protect itself against both malicious attacks and unintended mistakes by the operator

Autonomic computing meets SCADA security

© 2017 IEEE. National assets such as transportation networks, large manufacturing, business and health facilities, power generation, and distribution networks are critical infrastructures. The cyber threats to these infrastructures have increasingly become more sophisticated, extensive and numerous. Cyber security conventional measures have proved useful in the past but increasing sophistication of attacks dictates the need for newer measures. The autonomic computing paradigm mimics the autonomic nervous system and is promising to meet the latest challenges in the cyber threat landscape. This paper provides a brief review of autonomic computing applications for SCADA systems and proposes architecture for cyber security

Trust and reputation policy-based mechanisms for self-protection in autonomic communications

Currently, there is an increasing tendency to migrate the management of communications and information systems onto the Web. This is making many traditional service support models obsolete. In addition, current security mechanisms are not sufficiently robust to protect each management system and/or subsystem from web-based intrusions, malware, and hacking attacks. This paper presents research challenges in autonomic management to provide self-protection mechanisms and tools by using trust and reputation concepts based on policy-based management to decentralize management decisions. This work also uses user-based reputation mechanisms to help enforce trust management in pervasive and communications services. The scope of this research is founded in social models, where the application of trust and reputation applied in communication systems helps detect potential users as well as hackers attempting to corrupt management operations and services. These so-called “cheating services” act as “attacks”, altering the performance and the security in communication systems by consumption of computing or network resources unnecessarily

Vesta: A Secure and Autonomic System for Pervasive Healthcare

Accepted versio

Towards a Security, Privacy, Dependability, Interoperability Framework for the Internet of Things

A popular application of ambient intelligence systems constitutes of assisting living services on smart buildings. As intelligence is imported in embedded equipment, the system becomes able to provide smart services (e.g. control lights, airconditioning, provide energy management services etc.). IoT is the main enabler of such environments. However, the interconnection of these cyber-physical systems and the processing of personal data raise serious security and privacy issues. In this paper we present a framework that can guarantee Security, Privacy, Dependability and Interoperability (SPDI) in IoT. Taking advantage of the underlying IoT deployment, the proposed framework not only implements the requested smart functionality but also provide modelling and administration that can guarantee those SPDI properties. Moreover, we provide an application example of the framework in a smart building scenario

Detection of Malware Attacks on Virtual Machines for a Self-Heal Approach in Cloud Computing using VM Snapshots

Cloud Computing strives to be dynamic as a service oriented architecture. The services in the SoA are rendered in terms of private, public and in many other commercial domain aspects. These services should be secured and thus are very vital to the cloud infrastructure. In order, to secure and maintain resilience in the cloud, it not only has to have the ability to identify the known threats but also to new challenges that target the infrastructure of a cloud. In this paper, we introduce and discuss a detection method of malwares from the VM logs and corresponding VM snapshots are classified into attacked and non-attacked VM snapshots. As snapshots are always taken to be a backup in the backup servers, especially during the night hours, this approach could reduce the overhead of the backup server with a self-healing capability of the VMs in the local cloud infrastructure. A machine learning approach at the hypervisor level is projected, the features being gathered from the API calls of VM instances in the IaaS level of cloud service. Our proposed scheme can have a high detection accuracy of about 93% while having the capability to classify and detect different types of malwares with respect to the VM snapshots. Finally the paper exhibits an algorithm using snapshots to detect and thus to self-heal using the monitoring components of a particular VM instances applied to cloud scenarios. The self-healing approach with machine learning algorithms can determine new threats with some prior knowledge of its functionality

Security in Pervasive Computing: Current Status and Open Issues

Million of wireless device users are ever on the move, becoming more dependent on their PDAs, smart phones, and other handheld devices. With the advancement of pervasive computing, new and unique capabilities are available to aid mobile societies. The wireless nature of these devices has fostered a new era of mobility. Thousands of pervasive devices are able to arbitrarily join and leave a network, creating a nomadic environment known as a pervasive ad hoc network. However, mobile devices have vulnerabilities, and some are proving to be challenging. Security in pervasive computing is the most critical challenge. Security is needed to ensure exact and accurate confidentiality, integrity, authentication, and access control, to name a few. Security for mobile devices, though still in its infancy, has drawn the attention of various researchers. As pervasive devices become incorporated in our day-to-day lives, security will increasingly becoming a common concern for all users - - though for most it will be an afterthought, like many other computing functions. The usability and expansion of pervasive computing applications depends greatly on the security and reliability provided by the applications. At this critical juncture, security research is growing. This paper examines the recent trends and forward thinking investigation in several fields of security, along with a brief history of previous accomplishments in the corresponding areas. Some open issues have been discussed for further investigation